Thomson Reuters
Senior Legal Engineer, Legal Products Forward Deployed Engineering (FDE)
$95K–$203K
United States of America, Frisco, Texas +4 · Hybrid · Senior · Full-time · Posted Oct 26, 2026
- Location
- United States of America, Frisco, Texas
United States of America, New York, New York
Canada, Toronto, Ontario
United States of America, Ann Arbor, Michigan
United States of America, Eagan, Minnesota - Experience
- 5+ years total, including at least 2 years in legal practice at a law firm or in-house legal department, or in a legal technology product role.
- Education
- JD or LLB (required or strongly preferred).
About the job
Designs and deploys AI-powered legal workflows and tools with customers and cross-functional teams, evaluating their quality and helping legal teams adopt them.
What you'll do
- Design, prototype, test, and deploy AI solutions for legal workflows; build and iterate on prototypes and automations.
- Work directly with legal customers on discovery, pilots, onboarding, and enablement; train teams on AI tools and workflow integration.
- Evaluate legal AI outputs and develop benchmarks, rubrics, and regression checks to assess quality.
What they ask for
- JD or LLB (required or strongly preferred).
- 5+ years of total professional experience, including at least 2 years in legal practice or a legal technology product role.
- Fluency in legal terminology and experience working directly with or alongside legal teams.
- Strong knowledge of AI and LLM evaluation methodologies, advanced prompt-engineering skills, and experience assessing AI outputs for legal accuracy, relevance, reliability, and safety.
Nice to have
- Python scripting experience.
- Experience with legal technology platforms, AI-enabled legal workflows, or AI tools for legal practice areas.
Pay
$109,000 USD - $203,000 USD (base salary); $94,900 USD - $176,300 USD (base salary); $105,000 CAD - $155,000 CAD (base salary)
Tools
Python, AI, LLM
AI focus
Build and evaluate AI-powered legal workflows and tools; develop prompts and evaluation frameworks; assess AI output quality and enable legal teams to adopt AI.
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